from datetime import timedelta
from utils.operators.cluster_for_spark_sql_operator import SparkSqlOperator
from jms.ods.sqs.customer_service_call_record import jms_ods__customer_service_call_record

jms_dwd__dwd_customer_service_call_record_base_dt = SparkSqlOperator(
    task_id='jms_dwd__dwd_customer_service_call_record_base_dt',
    email=['rabie.zhuang@jtexpress.com', 'yl_bigdata@yl-scm.com'],
    name='jms_dwd__dwd_customer_service_call_record_base_dt_{{ execution_date | date_add(1) | cst_ds }}',
    sql='jms/dwd/dwd_customer_service_call_record_base_dt/execute.sql',
    pool_slots=2,
    #executor_cores=2,
    executor_cores=4,
    #executor_memory='8G',
    executor_memory='4G',
    driver_memory='4G',
    #num_executors=12,  # spark.dynamicAllocation.enabled 为 True 时，num_executors 表示最少 Executor 数
    num_executors=4,
    conf={
        # 'spark.dynamicAllocation.maxExecutors': 32,
        'spark.dynamicAllocation.maxExecutors'             : 5,
        'spark.sql.sources.partitionOverwriteMode': 'dynamic',
        'spark.dynamicallocation.enabled': 'true',
        'spark.dynamicAllocation.cachedExecutorIdleTimeout': 60,
        'spark.shuffle.service.enabled': 'true',
        'spark.sql.shuffle.partitions': 60
    },
    hiveconf={'hive.exec.dynamic.partition': 'true',
              'hive.exec.dynamic.partition.mode': 'nonstrict',
              'hive.exec.max.dynamic.partitions.pernode': 20,
              'hive.exec.max.dynamic.partitions': 20
              },
    yarn_queue='pro',
    execution_timeout=timedelta(minutes=60),
)

jms_dwd__dwd_customer_service_call_record_base_dt << [
    jms_ods__customer_service_call_record
]


